1. Field of the Invention
The present invention is directed to a method and apparatus for fuzzy control which takes into account the presence of noise at the input of the fuzzy controller in the formulation of the manipulated variable.
2. Description of the Prior Art
Fuzzy controllers are increasingly gaining significance since complex control-oriented problems can often be more simply solved with fuzzy controllers than in a conventional way. In practice, however, it is often not a clear, but instead a noise-infested, quantity that occurs as the control difference, this having a negative influence on the control behavior of the fuzzy controller when it is supplied to the controller in unfiltered form.
In known, theoretical works and applications that refer to fuzzy control (FC), sharp input quantities for the controller are always assumed, such as in a Mamdani controller (see "Applications of Fuzzy Algorithms for Control of a Simple Dynamic Plant," Mamdani, Proc. IEEE Vol. 121, No. 12, December 1974). The input quantity is scaled within the fuzzy controller and is then fuzzified (Mamdani, supra; also "An Introduction to Fuzzy Logic," Driankov et al. 1993, pp. 164-167); "fuzzification" meaning that the corresponding membership degrees are assigned to a normalized, sharp input quantity corresponding to the prescribed input reference fuzzy sets. Thereafter, the IF-THEN rules of the fuzzy controller are processed in a known way on the basis of the output reference fuzzy sets, with an output fuzzy set arising as the result. A sharp output quantity is produced from this output fuzzy set by defuzzification (for example, according to the center of area method). This is denormalized and emitted as an output to the path to be controlled as a physical manipulated variable. If noise is superimposed on the useful signal, then either the accidental signal value is further-processed in the fuzzy controller or the signal is pre-filtered.
The disadvantage of processing an unfiltered signal is that, as a static, non-linear transmission element, the fuzzy controller generally transmits the noise directly to the manipulated variable. When the signal path has a low-pass character, then the path itself acts as a filter. The setting means and path, however, are too highly loaded as a result so that the signal must generally be pre-filtered. The disadvantage of pre-filtering, however, is that a sliding average is in fact produced by the pre-filtering but the information abut the scatter of the signal and further statistical moments are lost. This information, however, allows conclusions to be made about the confidence of the individual measured value as well as about a potential asymmetry of the probability distribution density of these values. The latter can supply information about asymmetries in the measurement system but can also indicate systematic errors such as drift.